Titlebook: An Introduction to Object Recognition; Selected Algorithms Marco Alexander Treiber Book 2010 Springer-Verlag London Limited 2010 3D.Appear

BANAL

凹室

逢迎春日

Thyroid-Gland

美色花钱

斜谷

TEM

Geometric Correspondence-Based Approaches,ognition, e.g., from CAD data of the object shape. Typically, these methods are feature based, meaning that the object is characterized by a limited set of primitives called features. For example, the silhouette of many industrial objects can be modeled by a set of line segments and circular arcs as

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Three-Dimensional Object Recognition,ts have to be gripped by a robot from an unordered set of objects. Typically, such applications utilize sensor systems which allow for the generation of 3D data and perform matching in 3D space. Another way to determine the 3D pose of an object is to estimate the projection of the object location in

Mitigate

Flexible Shape Matching,to difficulties for deformable objects, specific approaches exist for such types of objects. These methods use parametric curves, which should approximate the object contour as good as possible. The parameters of the curve should offer enough degrees of freedom for accurate approximations. Two types

GROSS

Interest Point Detection and Region Descriptors,ety or the presence of heavy background clutter, occlusion, or varying illumination conditions, etc. These tough demands can be met by a two-stage strategy for the description of the image content: the first step consists of the detection of “interest points” considered to be characteristic. Subsequ